A lot of my work has been in the area of Pharmacoepidemiology. So it was with great interest that I read the commentary in the March 15th issue of the American Journal of Epidemiology by Dr. Noel Weiss. Dr. Weiss is a brilliant epidemiologist and so it is no surprise that his commentary clearly laid out the conceptual and practical problems associated with these studies.
The main problem is that people do not start (or stop) medication at random. They take medications to treat some underlying condition (thus leading to confounding by indication) and they stop for a number of reasons (including the treatment is completed). We know, for sure, that some drugs have withdrawal issues (consider morphine or SSRIs).
I've actually looked at this question with statin drug withdrawal and still worry about how successful we were at controlling for confounding factors (and, believe me, we did an enormous amount of analysis to see how robust the effect was).
But what is hard, in all of these studies. is separating the reason for stopping the drug from the outcome. If a participant stops an SSRI and has an increased risk of suicide is that a marker of:
1) The drug was not working to begin with
2) There were severe withdrawal issues
Separating these two factors is important! After all, if there is a period of increased danger than alternative monitoring for serious health events becomes an option.
But Dr. Weiss gives an excellent summary of all of the things that can go wrong in such analyses and why we need to be careful in interpreting them. So if you work in drug research at all, this article is definitely worth a look.